1 Outline

  EfeMOD Project

  Motivation and Objective

  Data

  Empirical Approach

  Results

  Conclusion / Outlook

2 EfeMOD

Empirisch fundierte Elektrizitätsmarkt-Modellierung mit Open Data

Project Entities:

Chair of Prof. Dr. Christoph Weber (Management Sciences and Energy Economics)

Chair of Prof. Dr. Florian Ziel (Data Science in Energy and Environment)

  Project Goal:

Use publicly available data (particularly ENTSO-E Transparency Platform) to estimate parameters for energy system and energy market models.

3 New Slide

Hallo World!

4 EfeMOD

5 Motivation and Objective

Identification of Power Plant Operation States Using Clustering

Gain Knowledge about the Power Plant Characteristics

  • Operation Points,
  • Efficiency
  • Capacity, etc.

This Presentation:

Identify Operation States:

  • Stable Operation
  • Startup
  • Minimum-Stable Operation, etc.

Provide these characteristics to other researchers

e.g. to estimate efficiency

6 Prior Partitioning

Model-Based Clustering of the Regions using mclust::Mclust in R.

  • Stable: 2-5 Clusters
  • Ramp Up: 2-4 Clusters
  • Ramp Down: 2-4 Clusters

Obtain finite mixture distribution:

\[\sum_{k=1}^{G}{\pi_k f_k (\mathbf{x}; \mathbf{\theta}_k)}\]

\(f_k\) Density of k’s component
\(\pi_k\) Mixture weights
\(\theta_k\) parameters of k’s density component

7 Try equations

\[ x =\sum_{i = 1}^{6} x_i \tag{1} \label{eq:einste} \]

\[ E = mc^2 \tag{2} \label{eq:eiein} \]

And here we reference equation (\(\ref{eq:einste}\)) again.

8 Energy Policy

According to recent studies, electricity markets are changing rapidly (Smith, 2020).

9 References

Smith, J. (2020). Energy markets and climate policy. Energy Economics, 88, 104739.